code: def test_logistic_derivative(backend_default):
      # bprop is on the output
      inputs = np.array([0, 1, -2]).reshape((3, 1))
      inputs = 1.0 / (1.0 + np.exp(-inputs))
      outputs = inputs * (1.0 - inputs)
      compare_tensors(
          Logistic(shortcut=False),
          inputs,
          outputs,
          deriv=True,
          tol=1e-7,
      )
  
imports: from math import tanh
  import numpy
  from neon import NervanaObject
  from neon.transforms import Identity, Rectlin, Softmax, Tanh, Logistic, Sign, PixelwiseSoftmax
  from utils import allclose_with_out
label_desc: Use image node_id 24 for calling a global function with example usage: test_logistic_derivative(backend_default) without return types